Recent advancements in biotechnology have led to the development of a unified strategy for single-cell multiomics analysis. This innovative approach, known as hybrid-scPMA, allows scientists to simultaneously characterize proteomic and metabolomic profiles at the individual cell level. Deciphering cellular heterogeneity remains a significant challenge in modern oncology. However, this one-shot hybrid-mode analysis provides a deep look into the same single cell. Consequently, clinicians and researchers can now better understand disease mechanisms and therapeutic efficacy with unprecedented clarity.

The hybrid-scPMA workflow integrates automated single-cell capture with a dual-acquisition mass spectrometry mode. Specifically, it uses data-independent acquisition (DIA) for analyzing digested peptides from proteins. Meanwhile, the data-dependent acquisition (DDA) mode identifies metabolites within the same liquid chromatography-mass spectrometry run. This combination effectively overcomes previous technical limitations regarding identification depth and sample loss. Furthermore, the simplified sample pretreatment and automated injection ensure higher reproducibility across diverse cell types.

Exploring Drug Mechanisms with Single-Cell Multiomics Analysis

Using this improved workflow, researchers identified an average of 3,510 protein groups and 255 metabolites in HepG2 cells. This represents a substantial improvement over earlier single-cell methods that often sacrificed one omic layer for another. Moreover, the researchers applied this technology to study HepG2 cells during sorafenib drug intervention. Sorafenib is a primary multi-kinase inhibitor used in treating advanced hepatocellular carcinoma. Therefore, this multiomics insight provides a clearer perspective on how individual liver cancer cells adapt or resist chemotherapy.

The study specifically resolved drug response characteristics at the single-cell level over time. By observing how proteins and metabolites shift simultaneously, the team uncovered new pathways involved in sorafenib resistance. These findings suggest that single-cell multiomics analysis will become a cornerstone for precision medicine. Specifically, it enables the identification of rare cell populations that drive treatment failure, which bulk analysis usually masks.

What is hybrid-scPMA and how does it work?

The hybrid-scPMA strategy is a "one-shot" method that uses two different mass spectrometry modes in a single run. It applies Data-Independent Acquisition (DIA) for proteins and Data-Dependent Acquisition (DDA) for metabolites. This allows for deep coverage of both molecular layers from the same single cell.

Why is this important for cancer treatment research?

Traditional analysis methods average the data from thousands of cells, which hides the unique behavior of individual cancer cells. This new method allows researchers to see exactly how one cell responds to a drug like sorafenib, helping to explain why some patients develop resistance while others respond well.

Disclaimer: This content is for informational and educational purposes only. It does not constitute medical advice or a professional recommendation. Refer to the latest local and national guidelines for clinical practice.

References

Wu J et al. Simultaneous In-Depth Single-Cell Proteomic and Metabolomic Analysis. Anal Chem. 2026 Apr 27. doi: 10.1021/acs.analchem.5c08090. PMID: 42043857.

He XY et al. Recent Advances in Mass Spectrometry-Based Single-Cell Multidimensional Multi-Omics Analysis. ResearchGate. 2025.

Tang X et al. Exploring the mechanism of resistance to sorafenib in hepatocellular carcinoma cell lines. Aging (Albany NY). 2020 Nov 21;12(22):22604-22619.